4 Foundations of Data-Driven HR | Analytics in HR

4 Foundations of Data-Driven HR

Each year, we survey hundreds of HR and business professionals and publish an HR Trends Report. In the survey, we ask questions about the state of...

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Each year, we survey hundreds of HR and business professionals and publish an HR Trends Report. In the survey, we ask questions about the state of metrics and analytics within HR departments. As a professional that focuses on this area, it is disappointing to see the yearly results.

In 2018, HR metrics & analytics was deemed the least effective area of HR (out of 23 different areas which include headache topics like change management and workforce planning). This is a trend that remains largely unchanged over the past five years.

When we dug deeper into the data, we could see that over one-third of HR departments are challenged to move beyond basic measurements of data like turnover.

Some leading organizations and HR functions have made large investments in their HR analytical teams but the reality for most other organization is that there is no large infusion of capital coming to them.

With these numbers in mind, we set out to understand what these HR departments could do to create immediate value for their organizations through better metrics & reporting, while still putting the foundations in place needed to enable more advanced analytics.

The Foundations of Data-Driven HR

So what does this foundation look like? We will answer this question by examining the data cycle that starts with data entry, moves into analysis, and ends in action.

Each portion of the cycle is underpinned by a foundational capability needed to ensure that the data can be turned into insights that drive results (see Figure 1). There are three prerequisites to ensure sufficient data quality:

  1. There is a need for proper data governance;
  2. Sufficient analytical capabilities are required to turn data into insight;
  3. The organization has to adopt data as part of their culture and decision making in order to ensure that those insights were actually used to make decisions.

Source

 
None of these three foundations are particularly earth-shattering. They did, however, stand out as the largest hurdles that the HR department needed to overcome to start getting value from their data.

A less obvious finding was a fourth foundational element that seemed key in enabling the HR functions to improve their metrics & analytic capabilities.

Organizations that did the above well, created a data plan that started at the end of the data cycle and worked backward. This meant identifying the most critical audience, understanding what decisions or problems data needed to be applied to, identifying the appropriate metrics or data points, and then working backwards through the data collection process.

This resulted in the implementation of limited, but targeted, data governance mechanisms to ensure the right data was being collected at the right level of accuracy.

This data plan meant that limited resources could be leveraged to produce a report or dashboard that actually fit the intended purpose, and was opened, viewed and used by the audience.

This successful application of data can help build momentum and support for larger investments into HR analytics. On top of that, by working through the other three foundational elements for a specific report or dashboard, HR departments are actively building the capabilities they need to scale in order to achieve more advanced analytics.

Data Plan at a Glance – Selecting Metrics that Matter

Audience: Most HR departments start with an executive leadership report, as these groups are typically clamoring for more information about the state of their workforce. However, it is important to evaluate different audiences as limited metric & analytic resources might be better served with a different focus.

For example, BI practitioners have already discovered the impact that giving front-line managers access to dashboards can have, as they are the closest to customers. The same is true for their relationship with the workforce. Consider the typical engagement process, where data is gathered, centralized, analyzed, a strategy is developed, then rolled down through the organization.

Compare this with a real-time engagement dashboard that managers can access to understand the current state of engagement within their teams and take immediate action at a local level.

Purpose: Identifying the purpose HR metrics will serve is one of the most valuable, and most neglected, activities that HR departments can take to create better dashboards & reports. Typically, there are three broad purposes worth examining:

  • Measure progress toward an objective
  • Inform a specific workforce decision
  • Track a critical workforce trend

Metric Selection: Once the purpose is identified, then it is time to select the right metrics to support it. Metrics should always be relevant (they relate to the need identified) and accurate (they reflect the true reality within the organization). Reports and dashboards should focus attention on the most important talent issues, so limit the number of metrics to less than 20 wherever possible. Small, easy to understand dashboards can produce big impacts!

Get Focused

HR departments in the early stages of their metric & analytics journey frequently focus only on what metrics they should report given the limited resources to track, analyze and present data. Our research showed that creating a data plan that works backward, from action to analysis and through to data collection, will ensure that the reports and dashboard being produced add value.

At the same time, this practice narrows the focus so that HR teams with limited resources can provide appropriate support for data-driven decisions, analytic capabilities, and data governance processes.


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